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Ask HN: Why Does the Smiling People A/B Test Not Work for Us?

3 points by znq 9y ago

We're developers at heart, and marketing doesn’t come naturally to us. We’ve read multiple articles on the positive effects of placing smiling people on pages. So we decided to try this out. Bugfender is available for several platforms, with our primary focus on iOS and Android. So we thought we’d A/B test our original platform pages with a version of a smiling person. We ran that test at a 50/50 ratio for 10 weeks, tracked the number page views and the number of clicks through to the the signup form from each version. Both versions were served on the same url, but for the purpose of this demonstration, we’ve separated them out, and you can view them here: - https://bugfender.com/platforms/ios - https://bugfender.com/platforms/ios-smiling - https://bugfender.com/platforms/android - https://bugfender.com/platforms/android-smiling Based on what we’d read, we expected to see some sort of increase (however small) in sign-up clicks when coming from the smiling versions. However the result we had we very different: • Android smiling CTR: 17.49% • Android normal CTR: 21.29% • iOS smiling CTR: 21.74% • iOS normal CTR: 31.43% * Percentage of users who clicked through to sign up after viewing each of the platforms page Over the course of 10 weeks, pages served with a smiling person always performed worse, averaging 5% for Android and 10% for iOS. We understand that there is no special formula that works for all, but we didn’t expect this, and we were wondering if anyone may have any insights or ideas as to why this might be? Could it have been the extended content? Or that the picture was too generic? Did it perhaps distract from the real data about the product? These are some of our thoughts, but as marketing is not our forte, we really have no idea and this is just speculation. We’re always keen to try out A/B test and experiments, so we’d love to hear any ideas or suggestions you have too. Thanks for taking the time to read this :)

tylerhou 9y ago
As a developer, being able to immediately see the value add from the example picture above the fold on the non-smiling version is a really big sell. In one glance I know what your software does and I know how I might need it. With the smiling version, it's a lot less clear what your software does and how I might use it. There's more text explaining the product, sure, but I don't really want to spend the cognitive effort reading it. Even after I have read it, I still don't really understand how your software solves my problem - at least not nearly as well as when you give an example image.
claudiulodro 9y ago
Your generic stock photo dude is not very appealing to developers. Try the test with that superhero bugfender lady instead of the bro and I bet you'll have better results.
dirktheman 9y ago
The smiling picture focuses on features ('remote logginf for IOS apps), where the normal page focuses on benefits ('Start Building Better iOS Apps Today'). Also, the layout/contrast is different. To get meaningful results out of your A/B testing the number of variables should be as little as possible. So if your premises is 'smiling people convert better than a picture of an iPhone' you should keep every other detail the same.
adzeds 9y ago
As one of the other comments has already touched on. You did not actually test smiling faces vs non-smiling faces as both the landing pages are very different in more than just one element. Also, from my experience your industry to better suited to different types of tests such as the value proposition and the selling of the benefits rather than the features of your product. Answer the visitors need/desire and they will sign up
- adzeds 9y ago
  I run a Conversion Rate Optimisation Agency and would be happy to help you design a new landing page to test as part of a free consultancy, in return for a review/testimonial of our work. Let me know if interested.
oldcynic 9y ago
My take: Generic stock photo dude draws the eye -- enough to distract from reading the copy as he stands out, but doesn't add anything. Why is he there? No idea, but he's not helping me figure out your service. Having a vague, unreadable, screenshot with some colours carelessly slapped over his image appears very amateurish to my eye. Thus I am actually put off a bug finding application. No point scrolling on, you're not telling me anything, it's just yet another generic page with generic empty sales words "enterprise grade encryption" - yawn (close page here). So I wouldn't get below the first fold before leaving. The non-smiling page immediately presents me a screen and use-case that looks like it might be useful to me. I'll spend a few seconds more and scroll down to look around a little.
saluki 9y ago
Like others have said try to keep your A/B tests the same except for the one change you are testing. If you haven't already check out patio11's book. https://www.kalzumeus.com/2012/12/21/i-wrote-a-book-on-conversion-optimization-for-software-companies/ https://www.kalzumeus.com/2012/12/21/i-wrote-a-book-on-conve... It still has lots of great info. His block, podcasts and comments here on HN are worth checking out too.
hluska 9y ago
I noticed some things and have some questions. 1.) What resolution/browser combination did you test? And what resolution/browser combinations visited the site during your a/b test? On my (old) iPhone, I don't see the smiling face at all. Instead, all I see is his elbow. 2.) Your copy is significantly different between the smiling and non smiling options. A/B testing gets messy as you change more variables. I think the copy on the non smiling option is much stronger. 3.) The design is quite different between the two options. The texture on the smiling version looks dirty and slightly pixelated. 4.) How big was your sample? One dirty secret of A/B testing is that you need fairly significant levels of traffic before a test has any meaning. Based on what I've seen, this isn't a very good study and I'd urge you not to consider it actionable. Rather, I'd recommend further study. When you design your next test, you should consider: A.) What percentage of users can see the smiling face? A decent analytics tool should give you all kinds of insight into resolutions, browsers and devices. Remember, if you're sending 50% of your traffic to the smiling face, but only 50% of those people can see it, you're not testing what you think you are. B.) Keep the copy and design elements identical. A/B testing gets messy as you start changing more than one thing. C.) Be careful with your sample size. If you only send a sample of 100 people to each version, you can't draw many (if any) conclusions and expect them to hold up under more traffic. If you do a proper test and still get those results, you should look into the people visiting your site and what their motivation is. Do you have any evidence to suspect that the people who are visiting you are currently trying to fix a bug? If so, is it possible the smiling face is too much for stressed out developers?